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Improving Policy Learning via Language Dynamics Distillation

Cohere

Recent work has shown that augmenting environments with language descriptions improves policy learning.

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Research Cohere

ResearchWhen Personalization Meets Reality: A Multi-Faceted Analysis of Personalized Preference LearningCohere ResearchPrioritized Training on Points that are Learnable, Worth Learning, and Not Yet LearntCohere ResearchLanguage Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-ThoughtCohere ResearchOPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple EstimatorsCohere ResearchSoft-SVeRL: Self-Verified Reinforcement Learning with Soft RewardsCohere ResearchThe Reality of AI and BioriskCohere BlogsGet notifications for events on your tailnet with webhooksTailscale BlogsI learned to love the Same-Origin PolicyCss Tricks LearnDuckDB Python Quickstart (Part 2): Pandas, Arrow, Polars & Python UDFsMotherduck BlogsThis Month in the DuckDB Ecosystem: January 2025Motherduck BlogsUser-centric performance metricsWeb BlogsPicture This: Open Source AI for Image DescriptionFly Products & ServicesSeed Audio 1.0 - Cinematic AI Audio GenerationFal Products & ServicesPixal3D | Image to 3D Model API | Official API on falFal Products & ServicesSeedance 2.0 API Live on fal (April 2026)Fal BlogsDocker, JetBrains, and Zed: Building a Common Language for Agents and IDEsDocker EventsCloud Native Live: Kyverno 1.17 ReleaseCncf BlogsHow Teleperformance is training a global workforceSynthesia BlogsHow BD Rowa uses AI video to train 300+ technicians globallySynthesia BlogsHow to Speed Up eLearning Content ProductionSynthesia